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儿童癌症的心脏监测使用人工智能支持的心电图

Ivor B Asztalos^1,2, Amy Li³, Victoria L Vetter¹

¹Division of Pediatric Cardiology, Perelman School of Medicine at the University of Pennsylvania, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

European heart journal. Digital health

|November 21, 2025

概括

人工智能启用心电图 (AI-ECG) 可以预测儿童癌症患者的左心室缩功能障碍. 这种AI-ECG工具对癌症幸存者的长期心脏监测充满希望.

科学领域:

心脏病学心脏病学
人工智能的人工智能
在瘤学瘤学.

背景情况:

儿童癌症幸存者患有长期心血管并发症的风险增加,包括左心室缩功能障碍.
早期检测和监测心脏功能对于改善这种脆弱人群的结果至关重要.

研究的目的:

评估人工智能启用心电图 (AI-ECG) 模型在儿童癌症患者中预测左心室缩功能障碍 (LVSD) 的能力.
评估AI-ECG作为儿童癌症幸存者的长期心脏监测的潜在工具.

主要方法:

一个已建立的AI-ECG模型被内部测试 (447名患者) 和外部验证 (2964名患者) 来预测左心室喷射率 (LVEF) ≤50%和≤40%.
包括AUROC,灵敏度和负预测值在内的绩效指标与基于生物标志物的模型进行了比较.
基于AI-ECG风险评分对LVEF≤50%的患者死亡率进行了分析.

主要成果:

AI-ECG模型在内部和外部队列中表现一致,AUROCs在0.80-0.85之间,用于预测LVEF≤50%.
在预测LVSD方面,AI-ECG模型的表现优于基于基准生物标志物的模型.
与高AI-ECG风险分数的患者相比,与低分数的患者相比,患者的死亡率明显更高 (HR 3.1,P < 0.001).

结论:

人工智能启用心电图 (AI-ECG) 显示出作为儿童癌症幸存者的心脏监测数字生物标志物具有显著的前景.
AI-ECG可以有效预测左心室缩功能障碍,有助于儿童癌症患者的长期管理.
使用AI-ECG可能有助于识别高风险个体,通过及时的心脏干预可能提高存活率.

关键词:

在AI-ECG中.心脏瘤学 - 心脏瘤学心脏有毒性 - 心脏有毒性儿童癌症儿童癌症左心室的缩性功能障碍是什么

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